Event Details

The last time that we offered this class in Austin, it sold out with a considerable waitlist. When we heard that Paco was coming back to town for NI Week, we asked if he would give an encore presentation. Venue subject to change.

Paco Nathan, Chief Scientist at Concurrent and author of the upcoming O'Reilly book Enterprise Data Workflows, will be teaching a one day hands-on Introduction to Data Science. This class is based on his workshop for the SFBay ACM.

Course Description

Big Data, Data Science, Cloud Computing... Lots of exciting stuff, lots of media buzz, lots of confusing descriptions. For a programmer armed with a laptop and some knowledge of Bash, Python, Java – what is a good way to begin working with these new tools for handling large-scale unstructured data?

In addition to examining “How” things work, we will take a detailed look at “Why” did MapReduce emerge this way – what factors lead to the popular frameworks and what typical issues confront large-scale deployments – so that each student is prepared to make ongoing assessments and learnings as the field continues to grow and evolve.

Caveat: absolutely no Cygwin, it just doesn't work. If someone has Windows, they'll need a VM and be running Linux on it. Alternatively, I'll have a EC2 server running with several accounts, and the installs already done. RStudio however will run great on Windows.

There will be a few other installs that we perform during the class in class.

Speaker Bio:

Paco Nathan@pacoid is currently the Director of Data Science at Concurrent in SF, and a committer on the Cascading open source project. For over ten years, A 25 year veteran of the tech industry, for the last ten years Paco has led Data teams. Paco has a background in math/stats and distributed computing, and expertise in Hadoop, R, AWS, predictive analytics, machine learning, and NLP. Paco is author of the upcoming O'Reilly book: Enterprise Data Workflows with Cascading.Paco's Wikipedia PagePaco on Twitter, Linkedin, Slideshare, Github